Design validation plays a crucial role in the overall cost and time allocation
for product development. This is especially evident in high-value manufacturing
sectors like commercial vehicle electric drive systems or e-axles, where the
expenses related to sample procurement, testing complexity, and diverse
requirements are significant.
Validation methodologies are continuously evolving to encompass new technologies,
yet they must be rigorously evaluated to identify potential efficiencies and
enhance the overall value of validation tests. Simulation tools have made
substantial advancements and are now widely utilized in the development phase.
The integration of simulation-based or simulation-supported validation processes
can streamline testing timelines and sample quantities, all the while upholding
quality standards and minimizing risks when compared to traditional methods.
This study examines various scenarios where the implementation of advanced
techniques has led to a reduction in the e-axle design validation plan (DVP),
particularly in relation to the start of production (SOP) decision-making
quality gates.
Many DVPs incorporate tests in a specific order to enhance the validation impact
of each sample and to guarantee that preconditioning tests are implemented when
necessary. An instance of preconditioning is subjecting a system to thermal
cycling. Thermal cycle preconditioning ensures that the sample accurately
represents a real-world system when undergoing sealing-related tests, such as
ingress protection testing according to ISO 20653 [1]. Assessing the necessary thermal cycling to “bed-in” a
sample would be highly elaborate using a physical sample, but it is a
straightforward aspect to extract from modern finite element analysis (FEA). A
case study will be presented to evaluate the minimum required thermal cycling
and determine the cost savings for the DVP.
Furthermore, the validation supported by simulations will be showcased in the
context of accelerated lifetime testing. Often, accelerating such tests
necessitates a balance between the distribution of damages and the overall
testing duration. By incorporating safety factors from simulations as an initial
input, the distribution of damages can be adjusted to allow for some
over-testing on more secure components, thereby reducing the overall testing
time.
Efficiency assessment will additionally be considered for virtual validation due
to the complexity of the measurement and data acquisition, contributing to
measurement uncertainty. Furthermore, simulation-based validation will be
considered for the case of lubrication testing, which can be hampered by a
largely qualitative assessment criteria.
Overall, these scenarios will be evaluated for their potential to streamline the
overall DVP process in terms of testing time, sample quantity, and critical path
duration. This underscores the potential benefits of leveraging advanced DVP
techniques for cost and time savings.
